When generating a video spliced

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Material contextual relevance: Since the video is spliced ​​together from multiple materials, if the AI ​​cannot understand the relationship between the materials and uses contradictory materials during the animation/video editing process, it will affect the final film effect. ii) Material copyright: The generated animation/video clips are derived from other video materials and may involve copyright issues. Tools need to solve and circumvent the identification of infringing content. iii) Size of material library: The size of the material library directly affects the effectiveness of this


type of video generation tool and the diversity of generated videos. Afghanistan WhatsApp Number A huge material library requires a large amount of copyright resources or content platform support, thereby building a "network effect" for the tool, while a smaller material library will limit the effectiveness of the tool. Therefore, it is easier for content giants to do better with AI tools in this direction. iv) Accuracy of search matches: Animation/video analysis AI has limited understanding of animation/video content, which leads to accuracy issues in search matching results, and there may be a certain gap between the images envisioned by users.  ​​from multiple animations/video clips, accuracy issues can stack up, causing the finished animation/video to





deviate from the original vision. These problems result in AI product tools related to material search and matching not being so easy to use at present. ) Text/pictures and videos: Sora belongs to the AI ​​direction of text/pictures and videos . Before the release of Sora, there were related tools on the market such as Pika, RunwayGen, and Stable Video Diffusion, which could generate a few seconds of video/animation based on user input of text or static images. However, there are obvious flaws in the text/picture generating video AI tools currently on the market , such as: i) Failure to understand the physical world: